Multivariate pattern analysis (MVPA) or brain decoding methods have become standard
practice in analyzing fMRI data. Although decoding methods have been extensively applied …

Parsing a cognitive task into a sequence of operations is a central problem in cognitive
neuroscience. We argue that a major advance is now possible owing to the application of …

Understanding object representations requires a broad, comprehensive sampling of the
objects in our visual world with dense measurements of brain activity and behavior. Here …

The curse of dimensionality plagues models of reinforcement learning and decision making.
The process of abstraction solves this by constructing variables describing features shared …

How we attend to objects and their features that cannot be separated by location is not
understood. We presented two temporally and spatially overlapping streams of objects …

Within a fraction of a second of viewing a face, we have already determined its gender, age
and identity. A full understanding of this remarkable feat will require a characterization of the …

Feedforward neural networks provide the dominant model of how the brain performs visual
object recognition. However, these networks lack the lateral and feedback connections, and …

For decades, the extent to which visual imagery relies on the same neural mechanisms as
visual perception has been a topic of debate. Here, we review recent neuroimaging studies …

Any cognitive function is mediated by a network of many cortical sites whose activity is
orchestrated through complex temporal dynamics. To understand cognition, we need to …

Research on emotion attribution has tended to focus on the perception of overt expressions
of at most five or six basic emotions. However, our ability to identify others' emotional states …